Rosetta@home
Rosetta@home is a Distributed computing project for protein structure prediction on the Berkeley Open Infrastructure for Network Computing (BOINC) platform, run by the David Baker (biochemist) at the University of Washington. Rosetta@home also aims to predict protein-protein docking and design new proteins with the help of over 86,000 volunteered computers processing over 77 teraFLOPS on average as of November 30, 2008. Though much of the project is oriented towards basic research on improving the accuracy and robustness of the proteomics methods, Rosetta@home also does applied research on Malaria, Alzheimer's disease and other pathologies. Like all BOINC projects, Rosetta@home uses idle computer processing resources from volunteers' computers to perform calculations on individual workunits. Completed results are sent to a central project server where they are validated and assimilated into project Databases. The project is Cross-platform, and runs on a wide variety of Hardware configurations. Users can view the progress of their individual protein structure prediction on the Rosetta@home screensaver. In addition to disease-related research, the Rosetta@home network serves as a testing framework for new methods in structural bioinformatics. These new methods are then used in other Rosetta-based applications, like RosettaDock and the Human Proteome Folding Project, after being sufficiently developed and proven stable on Rosetta@home's large and diverse collection of volunteer computers. Two particularly important tests for the new methods developed in Rosetta@home are the Critical Assessment of Techniques for Protein Structure Prediction (CASP) and Critical Assessment of Prediction of Interactions (CAPRI) experiments, biannual experiments which evaluate the state of the art in protein structure prediction and protein-protein docking prediction, respectively. Rosetta@home consistently ranks among the foremost docking predictors, and is one of the best tertiary structure predictors available. Computing platform Both the Rosetta@home application and the workunits distributed computing platform are available for the Microsoft Windows, Linux and Macintosh platforms (BOINC also runs on several other platforms, e.g. FreeBSD). Participation in Rosetta@home requires a Central processing unit (CPU) with a Clock speed of at least 500 MHz, 200 Megabytes of free disk space, 256 megabytes of physical memory, and Internet connectivity. As of December 1, 2008, the current version of the Rosetta application is 5.98, and the current recommended BOINC program version is 6.2.19. The software is freely licensed to the academic community and available to pharmaceutical companies for a fee. Ab initio modeling is considered an especially difficult category of protein structure prediction, as it does not use information from structural homology and must rely on information from sequence homology and modeling physical interactions within the protein. Rosetta@home has been used in CASP since 2006, where it was among the top predictors in every category of structure prediction in CASP7. These high quality predictions were enabled by the computing power made available by Rosetta@home volunteers. Increasing computational power allows Rosetta@home to sample more regions of conformation space (the possible shapes a protein can assume), which, according to Levinthal's paradox, is predicted to increase exponentially with protein length. Rosetta@home is also used in protein docking prediction, which determines the structure of multiple complexed proteins, or quaternary structure. This type of protein interaction affects many cellular functions, including antigen–antibody and enzyme–inhibitor binding and cellular import and export. Determining these interactions is critical for Drug design. Rosetta is used in the Critical Assessment of Prediction of Interactions (CAPRI) experiment, which evaluates the state of the protein docking field similar to how CASP gauges progress in protein structure prediction. The computing power made available by Rosetta@home's project volunteers has been cited as a major factor in Rosetta's performance in CAPRI, where its docking predictions have been among the most accurate and complete. In early 2008, Rosetta was used to computationally design a protein with a function never before observed in nature. This was inspired in part by the retraction of a high-profile paper from 2004 which originally described the computational design of a protein with improved enzymatic activity compared to its natural form. The 2008 research paper from David Baker's group describing how the protein was made, which cited Rosetta@home for the computational resources it made available, represented an important proof of concept for this protein design method. Numerous minor research projects are described in David Baker's Rosetta@home journal. Alzheimer's disease A component of the Rosetta software suite, RosettaDesign, was used to accurately predict which regions of amyloidogenic proteins were most likely to make amyloid-like fibrils. By taking hexapeptides (six amino acid-long fragments) of a protein of interest and selecting the lowest energy match to a structure similar to that of a known fibril forming hexapeptide, RosettaDesign was able to identify peptides twice as likely to form fibrils as are random proteins. Rosetta@home was used to in the same study to predict structures for amyloid-like fibrils, a fibril-forming protein that has been postulated to cause Alzheimer's disease. Preliminary but as yet unpublished results have been produced on Rosetta-designed proteins that may prevent fibrils from forming, although it is unknown whether it can prevent the disease. Anthrax Another component of Rosetta, RosettaDock, was used in conjunction with experimental methods to model interactions between three proteins – lethal factor (LF), edema factor (EF) and protective antigen (PA) – that make up Anthrax toxin. The computational model accurately predicted docking between LF and PA, helping to establish which domains of the respective proteins are involved in the LF–PA complex. This insight was eventually used in research resulting in improved anthrax vaccines. Herpes simplex virus 1 RosettaDock was also used to model docking between an Antibody (Immunoglobulin G) and a surface protein expressed by Herpes simplex virus 1 (HSV-1) which serves to degrade the antiviral antibody. The protein complex predicted by RosettaDock closely agreed with the particularly difficult-to-obtain experimental models, leading researchers to conclude that the docking method has potential in addressing some of the problems that X-ray crystallography has with modeling protein-protein interfaces. HIV As part of research funded by a $19.4 million dollar grant by the Bill and Melinda Gates Foundation, Rosetta@home has been used in designing multiple possible vaccines for human immunodeficiency virus (HIV). Malaria In research involved with the Grand Challenges in Global Health initiative, Rosetta has also been used to computationally design novel homing endonuclease proteins, which could eradicate Anopheles gambiae or otherwise render the mosquito unable to transmit Malaria. Being able to model and alter protein–DNA interactions specifically, like those of homing endonucleases, gives computational protein design methods like Rosetta an important role in Gene therapy (which includes possible Cancer treatments). In that experiment, RosettaDock made a high-accuracy prediction for the docking between streptococcal pyogenic exotoxin A and a T cell-receptor β-chain, and a medium accuracy prediction for a complex between porcine α-amylase and a Camelid Antibody. While the RosettaDock method only made two acceptably accurate predictions out of seven possible, this was enough to rank it seventh out of nineteen prediction methods in the first CAPRI assessment. Despite this disadvantage to BOINC users competing for rank, Rosetta@home is fifth out of over 40 BOINC projects in terms of total credit. Rosetta@home users who predict protein structures submitted for the CASP experiment are acknowledged in scientific publications regarding their results. Users who predict the lowest energy structure for a given workunit are featured on the Rosetta@home Homepage as 'Predictor of the Day', along with any team of which they are a member. A 'User of the Day' is chosen at random each day to be on the homepage as well from users who have made a Rosetta@home profile. References External links * David Baker's Rosetta@home journal * BOINC Includes platform overview, as well as a guide for installing BOINC and attaching to Rosetta@home * BOINCstats – Rosetta@home Detailed contribution statistics * RALPH@home Website for Rosetta@home alpha testing project * Rosetta@home Project website * Rosetta@home video on YouTube Overview of Rosetta@home given by David Baker and lab members * Rosetta Commons Academic collaborative for development of the Rosetta platform Online Rosetta services * Robetta Protein structure prediction server * RosettaDesign Protein design server * RosettaDock Protein-protein docking server